Overview

Dataset statistics

Number of variables8
Number of observations2429
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory154.2 KiB
Average record size in memory65.0 B

Variable types

DateTime1
TimeSeries6
Boolean1

Timeseries statistics

Number of series6
Time series length2429
Starting point2010-01-04 00:00:00
Ending point2019-08-29 00:00:00
Period1 day, 10 hours and 50 minutes
2026-02-05T23:21:16.713596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:16.936763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

repaired? has constant value "False"Constant
adj close is highly overall correlated with close and 4 other fieldsHigh correlation
close is highly overall correlated with adj close and 4 other fieldsHigh correlation
high is highly overall correlated with adj close and 4 other fieldsHigh correlation
low is highly overall correlated with adj close and 4 other fieldsHigh correlation
open is highly overall correlated with adj close and 4 other fieldsHigh correlation
volume is highly overall correlated with adj close and 4 other fieldsHigh correlation
adj close is non stationaryNon stationary
close is non stationaryNon stationary
high is non stationaryNon stationary
low is non stationaryNon stationary
open is non stationaryNon stationary
volume is non stationaryNon stationary
adj close is seasonalSeasonal
close is seasonalSeasonal
high is seasonalSeasonal
low is seasonalSeasonal
open is seasonalSeasonal
volume is seasonalSeasonal
Date has unique valuesUnique

Reproduction

Analysis started2026-02-05 23:21:11.940423
Analysis finished2026-02-05 23:21:16.597574
Duration4.66 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2429
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.0 KiB
Minimum2010-01-04 00:00:00
Maximum2019-08-29 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-05T23:21:17.123172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:17.245249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

adj close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2055
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.057913
Minimum26.209999
Maximum113.93
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-05T23:21:17.530637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.209999
5-th percentile42.193999
Q152.040001
median73.779999
Q393.879997
95-th percentile104.7
Maximum113.93
Range87.720001
Interquartile range (IQR)41.839996

Descriptive statistics

Standard deviation22.076472
Coefficient of variation (CV)0.3021777
Kurtosis-1.3862011
Mean73.057913
Median Absolute Deviation (MAD)21.059998
Skewness-0.027431717
Sum177457.67
Variance487.37062
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5980189812
2026-02-05T23:21:17.660522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-05T23:21:18.017475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-05T23:21:18.996673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
44.659999856
 
0.2%
93.959999084
 
0.2%
53.900001534
 
0.2%
48.520000463
 
0.1%
44.740001683
 
0.1%
81.253
 
0.1%
97.379997253
 
0.1%
102.66000373
 
0.1%
103.40000153
 
0.1%
49.560001373
 
0.1%
Other values (2045)2394
98.6%
ValueCountFrequency (%)
26.209999081
< 0.1%
26.549999241
< 0.1%
27.450000761
< 0.1%
27.940000531
< 0.1%
28.459999081
< 0.1%
29.040000921
< 0.1%
29.420000081
< 0.1%
29.440000531
< 0.1%
29.530000691
< 0.1%
29.639999391
< 0.1%
ValueCountFrequency (%)
113.93000031
< 0.1%
113.51999661
< 0.1%
112.86000061
< 0.1%
112.79000091
< 0.1%
112.76000211
< 0.1%
112.29000091
< 0.1%
112.27999881
< 0.1%
112.20999911
< 0.1%
111.44999691
< 0.1%
111.05000311
< 0.1%
2026-02-05T23:21:17.782796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2055
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.057913
Minimum26.209999
Maximum113.93
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-05T23:21:19.870590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.209999
5-th percentile42.193999
Q152.040001
median73.779999
Q393.879997
95-th percentile104.7
Maximum113.93
Range87.720001
Interquartile range (IQR)41.839996

Descriptive statistics

Standard deviation22.076472
Coefficient of variation (CV)0.3021777
Kurtosis-1.3862011
Mean73.057913
Median Absolute Deviation (MAD)21.059998
Skewness-0.027431717
Sum177457.67
Variance487.37062
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5980189812
2026-02-05T23:21:20.002662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-05T23:21:20.360068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-05T23:21:21.350038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
44.659999856
 
0.2%
93.959999084
 
0.2%
53.900001534
 
0.2%
48.520000463
 
0.1%
44.740001683
 
0.1%
81.253
 
0.1%
97.379997253
 
0.1%
102.66000373
 
0.1%
103.40000153
 
0.1%
49.560001373
 
0.1%
Other values (2045)2394
98.6%
ValueCountFrequency (%)
26.209999081
< 0.1%
26.549999241
< 0.1%
27.450000761
< 0.1%
27.940000531
< 0.1%
28.459999081
< 0.1%
29.040000921
< 0.1%
29.420000081
< 0.1%
29.440000531
< 0.1%
29.530000691
< 0.1%
29.639999391
< 0.1%
ValueCountFrequency (%)
113.93000031
< 0.1%
113.51999661
< 0.1%
112.86000061
< 0.1%
112.79000091
< 0.1%
112.76000211
< 0.1%
112.29000091
< 0.1%
112.27999881
< 0.1%
112.20999911
< 0.1%
111.44999691
< 0.1%
111.05000311
< 0.1%
2026-02-05T23:21:20.126204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

high
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2002
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.003668
Minimum27.48
Maximum114.83
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-05T23:21:22.072733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum27.48
5-th percentile43.056
Q152.860001
median74.75
Q394.699997
95-th percentile105.59
Maximum114.83
Range87.350002
Interquartile range (IQR)41.839996

Descriptive statistics

Standard deviation22.121404
Coefficient of variation (CV)0.29892307
Kurtosis-1.3974261
Mean74.003668
Median Absolute Deviation (MAD)21.160004
Skewness-0.027272919
Sum179754.91
Variance489.3565
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6105491617
2026-02-05T23:21:22.206497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-05T23:21:22.761402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-05T23:21:23.743188image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
46.529998785
 
0.2%
94.639999394
 
0.2%
52.779998784
 
0.2%
46.409999854
 
0.2%
97.819999694
 
0.2%
97.690002444
 
0.2%
48.740001684
 
0.2%
92.879997254
 
0.2%
48.200000764
 
0.2%
86.370002754
 
0.2%
Other values (1992)2388
98.3%
ValueCountFrequency (%)
27.479999541
< 0.1%
28.579999921
< 0.1%
29.219999311
< 0.1%
29.659999851
< 0.1%
30.209999081
< 0.1%
30.251
< 0.1%
30.610000611
< 0.1%
30.729999541
< 0.1%
31.180000311
< 0.1%
31.379999161
< 0.1%
ValueCountFrequency (%)
114.83000181
< 0.1%
114.18000031
< 0.1%
113.97000121
< 0.1%
113.48000341
< 0.1%
113.45999911
< 0.1%
113.40000151
< 0.1%
113.22000121
< 0.1%
113.18000031
< 0.1%
112.63999941
< 0.1%
112.48000341
< 0.1%
2026-02-05T23:21:22.323830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

low
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2037
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.049625
Minimum26.049999
Maximum112.25
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-05T23:21:24.462237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.049999
5-th percentile41.458
Q151.029999
median72.529999
Q392.93
95-th percentile103.862
Maximum112.25
Range86.200001
Interquartile range (IQR)41.900002

Descriptive statistics

Standard deviation21.943915
Coefficient of variation (CV)0.30456667
Kurtosis-1.3791155
Mean72.049625
Median Absolute Deviation (MAD)20.889999
Skewness-0.025077971
Sum175008.54
Variance481.53538
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5777285445
2026-02-05T23:21:24.591223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-05T23:21:25.102620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-05T23:21:26.099001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
92.860000614
 
0.2%
96.260002144
 
0.2%
96.510002144
 
0.2%
90.660003663
 
0.1%
95.209999083
 
0.1%
44.349998473
 
0.1%
903
 
0.1%
97.370002753
 
0.1%
85.110000613
 
0.1%
46.669998173
 
0.1%
Other values (2027)2396
98.6%
ValueCountFrequency (%)
26.049999241
< 0.1%
26.190000531
< 0.1%
26.950000761
< 0.1%
27.239999771
< 0.1%
27.739999771
< 0.1%
27.870000841
< 0.1%
28.209999081
< 0.1%
28.700000761
< 0.1%
28.729999541
< 0.1%
29.049999241
< 0.1%
ValueCountFrequency (%)
112.251
< 0.1%
111.69000241
< 0.1%
111.12000271
< 0.1%
111.08000181
< 0.1%
1111
< 0.1%
110.81999971
< 0.1%
110.70999911
< 0.1%
110.30000311
< 0.1%
110.11000061
< 0.1%
109.11000061
< 0.1%
2026-02-05T23:21:24.713346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

open
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2013
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.077098
Minimum27.299999
Maximum113.89
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-05T23:21:26.824649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum27.299999
5-th percentile42.096001
Q152.049999
median73.889999
Q393.879997
95-th percentile104.77
Maximum113.89
Range86.59
Interquartile range (IQR)41.829998

Descriptive statistics

Standard deviation22.058585
Coefficient of variation (CV)0.3018536
Kurtosis-1.3872832
Mean73.077098
Median Absolute Deviation (MAD)21.040001
Skewness-0.027460119
Sum177504.27
Variance486.58116
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6149818002
2026-02-05T23:21:26.957716image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-05T23:21:27.314066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-05T23:21:28.527334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
99.199996955
 
0.2%
93.489997865
 
0.2%
95.790000924
 
0.2%
97.300003054
 
0.2%
66.620002754
 
0.2%
49.310001374
 
0.2%
51.950000763
 
0.1%
52.049999243
 
0.1%
58.319999693
 
0.1%
59.270000463
 
0.1%
Other values (2003)2391
98.4%
ValueCountFrequency (%)
27.299999241
< 0.1%
27.340000151
< 0.1%
28.329999921
< 0.1%
28.350000381
< 0.1%
28.360000611
< 0.1%
29.079999921
< 0.1%
29.139999391
< 0.1%
29.200000761
< 0.1%
29.719999311
< 0.1%
29.751
< 0.1%
ValueCountFrequency (%)
113.88999941
< 0.1%
113.27999881
< 0.1%
113.12999731
< 0.1%
112.98000341
< 0.1%
112.81999971
< 0.1%
112.33999631
< 0.1%
112.15000151
< 0.1%
111.88999941
< 0.1%
111.37000271
< 0.1%
110.68000031
< 0.1%
2026-02-05T23:21:27.077853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

repaired?
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
False
2429 
ValueCountFrequency (%)
False2429
100.0%
2026-02-05T23:21:29.182913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

volume
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2422
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean416264.69
Minimum48516
Maximum1311000
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-05T23:21:29.287837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum48516
5-th percentile150892.4
Q1253456
median351309
Q3562639
95-th percentile806778.2
Maximum1311000
Range1262484
Interquartile range (IQR)309183

Descriptive statistics

Standard deviation212452.92
Coefficient of variation (CV)0.51037939
Kurtosis0.072685613
Mean416264.69
Median Absolute Deviation (MAD)129584
Skewness0.81925234
Sum1.0111069 × 109
Variance4.5136242 × 1010
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.2371922806
2026-02-05T23:21:29.432563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-05T23:21:29.798908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-05T23:21:30.963523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2263432
 
0.1%
2975222
 
0.1%
3179972
 
0.1%
1324272
 
0.1%
5988362
 
0.1%
2500382
 
0.1%
8956432
 
0.1%
4810341
 
< 0.1%
4504721
 
< 0.1%
5422541
 
< 0.1%
Other values (2412)2412
99.3%
ValueCountFrequency (%)
485161
< 0.1%
518771
< 0.1%
656661
< 0.1%
837021
< 0.1%
846271
< 0.1%
908241
< 0.1%
913981
< 0.1%
927801
< 0.1%
931301
< 0.1%
952701
< 0.1%
ValueCountFrequency (%)
13110001
< 0.1%
12535661
< 0.1%
11823271
< 0.1%
11735811
< 0.1%
11473891
< 0.1%
11362321
< 0.1%
11354401
< 0.1%
11249591
< 0.1%
11080521
< 0.1%
10956431
< 0.1%
2026-02-05T23:21:29.559253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

Interactions

2026-02-05T23:21:15.944071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:13.686700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.121266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.545508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.972413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.520148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:16.023933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:13.760529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.191061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.614746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.044371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.589025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:16.104341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:13.831424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.259714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.683499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.236099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.657717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:16.182715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:13.901487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.328500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.753290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.303653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.727779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:16.262458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:13.971909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.397027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.822892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.372329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.795353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:16.341654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.040639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.464379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:14.893780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.440584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-05T23:21:15.865804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-05T23:21:31.641252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
adj closeclosehighlowopenvolume
adj close1.0001.0000.9990.9990.997-0.602
close1.0001.0000.9990.9990.997-0.602
high0.9990.9991.0000.9990.999-0.596
low0.9990.9990.9991.0000.999-0.607
open0.9970.9970.9990.9991.000-0.600
volume-0.602-0.602-0.596-0.607-0.6001.000

Missing values

2026-02-05T23:21:16.463826image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-05T23:21:16.546062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Dateadj closeclosehighlowopenrepaired?volume
2010-01-042010-01-0481.51000281.51000281.68000079.62999779.629997False263542
2010-01-052010-01-0581.76999781.76999782.00000080.94999781.629997False258887
2010-01-062010-01-0683.18000083.18000083.51999780.84999881.430000False370059
2010-01-072010-01-0782.66000482.66000483.36000182.26000283.199997False246632
2010-01-082010-01-0882.75000082.75000083.47000181.80000382.650002False310377
2010-01-112010-01-1182.51999782.51999783.94999781.95999982.879997False296304
2010-01-122010-01-1280.79000180.79000182.33999679.91000482.070000False333866
2010-01-132010-01-1379.65000279.65000280.66999878.37000380.059998False401627
2010-01-142010-01-1479.38999979.38999980.36000178.91999879.629997False275404
2010-01-152010-01-1578.00000078.00000079.30999877.69999779.199997False200555
Dateadj closeclosehighlowopenrepaired?volume
2019-08-162019-08-1654.86999954.86999955.66999854.25999854.740002False168345
2019-08-192019-08-1956.20999956.20999956.41000054.84000054.959999False113571
2019-08-202019-08-2056.34000056.34000056.59999855.27999956.099998False659258
2019-08-212019-08-2155.68000055.68000057.13000155.54999956.049999False704035
2019-08-222019-08-2255.34999855.34999856.45999954.84999855.939999False621573
2019-08-232019-08-2354.16999854.16999855.59999853.24000255.349998False807151
2019-08-262019-08-2653.63999953.63999955.25999852.95999953.250000False679022
2019-08-272019-08-2754.93000054.93000055.72000153.68999953.759998False596624
2019-08-282019-08-2855.77999955.77999956.75000055.34000055.709999False674048
2019-08-292019-08-2956.70999956.70999956.88999955.43000055.880001False630760